# reads excel data sheet
data <- read.csv("../data/study4.csv") # reads data
data_sat <- read.csv("../data/raw/stage3_satisfaction.csv") # reads in satisfaction data
# summary(data) # explore the data types, missing data and typos
data <- data %>%
mutate(gender = ifelse(gender == "m", "m", "f")) # corrects an issuewith extra space in "f "
data$gender <- as.factor(data$gender)
data$pp_number <- as.factor(data$pp_number)
data$condition <-as.factor(data$condition)
# mood data
mood1 <- read.csv("../data/raw/stage1_mood.csv") %>%
dplyr::select(subject, stimulusitem2, response)%>%
rename(response1=response, feeling = stimulusitem2)%>%
mutate(stage = 1)%>%
filter(subject != 6666)
mood2 <- read.csv("../data/raw/stage2_mood.csv") %>%
dplyr::select(subject, stimulusitem2, response)%>%
rename(response2=response, feeling = stimulusitem2)%>%
mutate(stage = 2)%>%
filter(subject != 6666)
mood3 <- read.csv("../data/raw/stage3_mood.csv") %>%
dplyr::select(subject, stimulusitem2, response) %>%
rename(response3=response, feeling = stimulusitem2)%>%
mutate(stage = 3)%>%
filter(subject != 6666)
mood_dat <- inner_join( mood1, mood2,
by = c("subject", "feeling"),
keep = FALSE)%>%
inner_join(., mood3,
by = c("subject", "feeling"),
keep = FALSE)%>%
dplyr::select(- starts_with("stage")) %>%
pivot_longer(cols = response1:response3,
names_to ="stage",
values_to = "rating")%>%
pivot_wider(names_from = "feeling",
values_from ="rating" )%>%
mutate(alert = (alert +strong + `clear-headed` + `well-coordinated` + energetic + `quick-witted` + attentive + proficient + interested )/9,
content =(contented + tranquil + amicable + gregarious)/4,
calm =(calm + relaxed)/2)
#`clear-headed` + `well-coordinated` + energetic + `quick-witted` + attentive + proficient + interested
# qualtrics data
#mainly info about drinking
data_q<- read.csv("../data/other/study_4Q.csv")%>%
dplyr::select(Q21, gender, age, Q15, Q16)%>%
rename(subject = Q21,
units = Q15,
units_beer = Q16)%>%
mutate(subject = as.numeric(subject),
condition = subject %/% 1000)%>%
filter(!is.na(subject))%>%
mutate(subject = as.factor(subject),
gender=as.factor(gender),
age = as.numeric(age),
units = as.numeric(units),
units_beer = as.numeric(units_beer))%>%
filter( subject != "6666")
# expectations & perception of taste/flavour
taste_dat <- read.csv("../data/raw/stage1_perception.csv")%>%
dplyr::select(subject, trialcode, response)%>%
rename(Epercept = trialcode, expected = response)
taste_dat$Epercept<- as.factor(taste_dat$Epercept)
expect_dat<- read.csv("../data/raw/stage1_expectations.csv")%>%
dplyr::select(subject, trialcode, response, stimulusitem3)%>%
filter(stimulusitem3 == "extremely")%>%
dplyr::select(- stimulusitem3)%>%
rename(percept = trialcode, perceived = response)
expect_dat$percept<- as.factor(expect_dat$percept)
# satisfaction data
#merge data_sat and expect_dat
satis_datP <- data_sat %>%
dplyr::select(subject, trialcode, response)%>%
dplyr::filter(trialcode == "VAS")
satis_datE <- expect_dat %>%
dplyr::filter(percept == "VAS_satisE_VAS")
wtp_dat <- data_sat %>%
filter(trialcode == "VAS_wtp")%>%
dplyr::select(subject, response)
# ITT data
itt_s1 <-read.csv("../data/summaries/stage1_ITT.csv")%>%
dplyr::select(script.subjectid, expressions.propcorrect_stim1:expressions.propcorrect_stim13)%>%
mutate(stage1 = 1)%>%
rename(subject = script.subjectid)%>%
rename_at(vars(matches("^expressions")), ~ str_remove(.,"^expressions.propcorrect_")) %>%
pivot_longer(cols = starts_with("stim") ,
names_to = "stimulus" ,
values_to = "correct")
itt_s2 <-read.csv("../data/summaries/stage2_ITT.csv")%>%
dplyr::select(script.subjectid, expressions.propcorrect_stim1:expressions.propcorrect_stim13)%>%
mutate(stage2 = 2)%>%
rename(subject = script.subjectid)%>%
rename_at(vars(matches("^expressions")), ~ str_remove(.,"^expressions.propcorrect_"))%>%
pivot_longer(cols = starts_with("stim") ,
names_to = "stimulus" ,
values_to = "correct")
itt_s3 <-read.csv("../data/summaries/stage3_ITT.csv")%>%
dplyr::select(script.subjectid, expressions.propcorrect_stim1:expressions.propcorrect_stim13)%>%
mutate(stage3 = 3)%>%
rename(subject = script.subjectid)%>%
rename_at(vars(matches("^expressions")), ~ str_remove(.,"^expressions.propcorrect_"))%>%
pivot_longer(cols = starts_with("stim") ,
names_to = "stimulus" ,
values_to = "correct")
itt_dat <- inner_join(itt_s1, itt_s2,
by = c("subject","stimulus"),
keep = FALSE,
suffix = c(".1", ".2"))%>%
inner_join(., itt_s3,
by = c("subject", "stimulus"),
keep = FALSE) %>%
pivot_longer(cols = starts_with("correct") ,
names_to = "stage",
values_to = "correct")%>%
dplyr::select(-c( stage1, stage2, stage3))%>%
mutate( stage = case_when(stage == "correct.1" ~ 'stage 1',
stage == "correct.2" ~ "stage 2",
stage == "correct" ~ "stage 3"))%>%
mutate(condition = subject %/% 1000) %>%
mutate(alcohol = if_else((condition%%2)==1, "alcoholic", "non-alcoholic"))%>%
mutate(focus = case_when(condition == 1 ~ 'control',
condition == 2 ~ 'control',
condition == 3 ~ 'hedonic',
condition == 4 ~ 'hedonic',
condition == 5 ~ 'utilitarian',
condition == 6 ~ 'utilitarian'))